The South Sudanese government has called on Tanzania to send Swahili teachers to the country as it introduces the language in school curriculum ahead of its adoption as an official language.
The request was made by South Sudanese Vice President Taban Deng Gai on the sidelines of the just ended African Union Summit on Tuesday, Tanzania's Vice President Samia Hassan said in a statement cited by local media The Citizen.
South Sudan also requested for assistance in other sectors of its economy including health, agriculture and security, the statement added.
Swahili has been adopted as the official language for the East African Community (EAC), of which South Sudan is its latest member after it deposited the instruments of ratification on the Accession to the EAC Treaty last year.
The language is part of the commitments entered in 2007 by the EAC, whose three founders – Kenya, Uganda and Tanzania – use Swahili as their official language alongside English.
Rwanda is yet to make it its fourth official language after national language Kinyarwanda, French and English.


How was Latios able to outspeed me?
I was battling a Latios with my Swampert, (wi-fi battle) and Swampert's quick claw activates, but Latios still moved first without any speed boosts.
What was the move swampert used?
The only reason I could think of here is if either the Latios used a move that has priority over the one you sued or if your move had negative priority, like Roar(-6).
>A hold item that gives the holder a 20% chance of going first in its priority bracket and ignores the effects of Trick Room.
It only works if both moves are in the same priority bracket, meaning they both have 0, +1, +2 etc. priority. If one has a higher priority it just ignores the Quick claw.
It's not just taking your comment, it's looking up what Quick claw does and taking your example of Roar.
I mentioned in my answer that Latios could have used priority as well.
Of course it can be a bug, but saying that won't help much. And ofc he knows what Quicj claw does, maybe he just didn't know that it only effects the priority if it's in the same priority bracket to begin with.
Would a ninjask level one be able to outspeed a munchlax level 100 with six speed boosts?
If you release Latios/Latias will you be able to soar?


text:
Be Brave: A Wife's Journey Through Caregiving
By Florrie Munat
ISBN 13: 978-0-9990092-0-8
Trim Size: 6" x 9"
Publisher: Fantail Publishing LLC
How difficult it is to watch someone lose their mental faculties. How much harder when this someone is beloved, central to your life. Be Brave: A Wife's Journey Through Caregiving is Florrie's Munat's story of caring for her husband Chuck. Florrie struggles with anguish, shock, anger, and grief as Chuck's dementia progresses and turns her world upside-down. But through time, Florrie clears a ground of acceptance within herself. And in that clearing, compassion grows—allowing for times of beauty, humor, and profound love.
Florrie Munat spent six years caregiving for her husband while he struggled with dementia. She published three non ction books and articles that appeared in Highlights for Children, Cricket, Scholastic Dynamath, Storytelling, and Microsoft's My Personal Tutor software, among others. She has written over 100 book reviews for young adults and recorded hundreds of short stories and audiobooks for the Washington Talking Book & Braille Library. A former librarian, English teacher, and university press worker, she lives on an island in Puget Sound where she is writing a memoir about grieving.
Publication Date: 1/1/1900

redpajama_set_name: RedPajamaCommonCrawl


text:
Alex Speier
Tom Brady has dominated against Dick LeBeau's defenses
By Alex Speier Globe Staff,January 10, 2018, 1:19 a.m.
New England is 7-2 in its last nine contests against Dick LeBeau defenses.Mark Humphrey/Associated Press
One ticket, every season: the "Season Ticket" podcast
Tom Brady's introduction to Titans defensive coordinator Dick LeBeau and his zone-blitz scheme was a moment of such infamy that it remains easy to remember after nearly 15 years.
In Week 1 of the 2003 season, against a Bills team for whom LeBeau was an assistant coach overseeing the defense, Brady turned in the worst performance of his sterling career. At a time when the Patriots were dazed by the release of Lawyer Milloy, Brady was picked off four times, including a pick-6 by monster defensive lineman Sam Adams. His 22.5 passer rating in that 31-0 loss in Buffalo was the worst of his career, while his four picks matched a career-worst.
In that game, Brady and the Patriots looked discombobulated, confused by the cleverly disguised blitzes and varied personnel schemes that could feature a 370-pound mountain like Adams dropping back in coverage. That New England team wasn't the only one to suffer such a fate against LeBeau, a Hall of Fame defensive back who is now 45 years into his coaching career.
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"He's a great coach, was a great player," Patriots coach Bill Belichick said in a conference call this week. "He's been a tremendous asset and has made so many contributions to the game of professional football in the National Football League.
"There are few coaches that I think you could put above him in terms of the amount of what he's accomplished and how much respect I have for him, how much respect all of us in the league have for him and what he's done.
"He's had a tremendous career. He's made this game a better game and he's done a lot for the coaching profession."
Yet while the Patriots hold LeBeau in high regard, that initial introduction of Brady to Tennessee's current defensive guru represents an aberration. At the end of the 2003 regular season, Brady and the Patriots flipped the script with their own 31-0 win over the Bills on the way to their second Super Bowl title. In the rematch, Brady went 21 of 32 for 204 yards, with 4 touchdowns and no picks.
In nine games beginning with that contest, Brady and the Patriots consistently have dissected LeBeau's defensive schemes with the Bills, Steelers, and most recently Titans. New England is 7-2 in its last nine contests against LeBeau, averaging 32.6 points per game.
In those contests, Brady has thrown for 23 touchdowns and just three interceptions, completing 68 percent of his pass attempts, averaging exactly 300 yards per game, and posting a passer rating of 112.3. Brady hasn't thrown an interception in any of his last five games against LeBeau's defenses.
Tom Brady's performances against Dick LeBeau-coached defenses Brady is 7-3 when opposing defenses where LeBeau is the coordinator
Comp %
9/7/2003 Bills L 0-31 14 28 50.0 123 0 4 22.5 2
12/27/2003 Bills W 31-0 21 32 65.6 204 4 0 122.9 2
10/31/2004 Steelers L 20-34 25 43 58.1 271 2 2 72.9 4
1/23/2005* Steelers W 41-27 14 21 66.7 207 2 0 130.5 2
9/25/2005 Steelers W 23-20 31 41 75.6 372 0 1 92.7 3
12/9/2007 Steelers W 34-13 32 46 69.6 399 4 0 125.2 0
11/14/2010 Steelers W 39-26 30 43 69.8 350 3 0 117.4 0
10/30/2011 Steelers L 17-25 24 35 68.6 198 2 0 101.8 3
12/20/2015 Titans W 33-16 23 35 65.7 267 2 0 107.7 2
TOTAL 7-3 237 357 66.4 2823 23 7 103.7 21
SOURCE: Stats Inc., Pro-Football-Reference.com
*AFC title game
Part of Brady's success against LeBeau likely stems from his mastery of blitzes. The quarterback's reads are so quick that his ability to find the open receiver typically exceeds the defense's ability to get to him, particularly in zone schemes that create open pockets in which to target receivers.
That has helped Brady shred blitzes from LeBeau-designed defenses in recent years. According to Stats Inc., in Brady's last five games against LeBeau's teams, he's 42 for 60 with 6 touchdowns, no picks, 2 sacks, and a 126.7 passer rating against blitzes.
Perhaps in deference to that, LeBeau has been more judicious in sending an extra rusher after Brady in recent years. After blitzing a whopping 38 times with the Steelers against Brady in December 2007 (a 34-13 Patriots win), LeBeau's teams have reduced their blitz totals in each of their last four games with New England. When the Titans faced Brady near the end of the 2015 regular season, they blitzed just 11 times in the 37 instances when the quarterback dropped back.
That said, it remains an open question whether LeBeau will remain relatively conservative in his blitz schemes this week. In a year when Julian Edelman hasn't been available as the ultimate safety valve against blitzes, the Patriots have been unusually ineffective against a release-the-hounds pursuit of their quarterback.
Whereas Brady posted ratings of 100.0 or better against the extra rusher from 2014-16 — including his NFL-leading mark of 126.7 in 2016 — he had just an 85.0 passer rating (22nd among qualifying quarterbacks) against blitzes this year.
Whether that struggle creates an opening for LeBeau and the Titans to stifle Brady remains to be seen. If the legendary defensive coach does identify a blueprint to control New England's passing offense, it will represent a distinct change of course from what has been a one-sided dynamic for most of Brady's career.
Alex Speier can be reached at alex.speier@globe.com. Follow him on twitter at @alexspeier.


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text:
Inclusive Jet Production, Parton Distributions,
and the Search for New Physics
Daniel Stump Joey Huston Jon Pumplin Wu-Ki Tung Department of Physics and Astronomy
East Lansing, MI 48824 H. L. Lai Department of Physics and Astronomy
East Lansing, MI 48824 Department of Science Education
Taipei Municipal Teachers College, Taiwan Steve Kuhlmann Argonne National Laboratory
Argonne, IL 60439 J. F. Owens Department of Physics
Jet production at the Tevatron probes some of the smallest distance scales currently accessible. A gluon distribution that is enhanced at large x compared to previous determinations provides a better description of the Run 1b jet data from both CDF and DØ. However, considerable uncertainty still remains regarding the gluon distribution at high x. In this paper, we examine the effects of this uncertainty, and of the remaining uncertainties in the NLO QCD theory, on jet cross section comparisons to Run 1b data. We also calculate the range of contributions still possible from any new physics. Predictions are also made for the expanded kinematic range expected for the ongoing Run 2 at the Tevatron and for the LHC.
††preprint: MSUHEP-030303
I Introduction: Jet cross sections at the Tevatron
II Uncertainty analysis of the cross section for inclusive jet production at the Tevatron
II.1 The Hessian method of uncertainty analysis
II.2 The Tevatron jet cross section
III Reliability of next-to-leading-order predictions
III.1 Scale dependence of the jet cross section
III.2 Fits with different scales
III.3 Threshold resummation
IV Room for New Physics in Run 1b
V Predictions for Run 2
V.1 The ratio of Run 2 to Run 1b cross sections
VI Inclusive jet production at the LHC
VII Conclusions
Jet production at the Tevatron probes the highest momentum transfer region currently accessible. As this region is potentially sensitive to a wide variety of new physics, there was great interest when the inclusive jet cross section measured by the CDF collaboration in Run 1b exhibited an excess in the highest ET range, when compared to NLO predictions using then-current parton distribution functions cdf1A . In an attempt to determine if conventional physics could explain the deviation, the CTEQ PDF fitting group carried out a global analysis using information from deep-inelastic scattering and Drell-Yan data, as well as from jet data from the Tevatron, but giving a higher statistical emphasis to the high ET jet data from CDF cteq4hj . NLO predictions using the resulting fit (CTEQ4HJ) reduced the size of the excess observed by CDF. The jet data from both CDF and DØ were also used in a more conventional fit (CTEQ4M) where no special emphasis was given to the high ET data cteq4 .
The dominant subprocess that contributes to jet production at high ET is quark-(anti)quark scattering. However, the quark distributions in the corresponding x range are very well constrained by the precise DIS and DY data used in the global fits. Only the gluon distribution has the flexibility to change significantly in the high x region, and indeed the gluon distribution increases by roughly a factor of 2 for x values of about 0.5 in the CTEQ4HJ fit. The gluon-quark scattering subprocesses increase from approximately 20% of the total jet cross section at high ET using CTEQ4M to 40% using CTEQ4HJ cteq4hj .
The next group of PDF's from CTEQ (CTEQ5) cteq5 also contained two sets: CTEQ5M, the standard lowest χ2 solution, and CTEQ5HJ, defined by a similar statistical enhancement applied to the high ET data from CDF cdf1b and DØ d01b .
More recently, DØ has measured the inclusive jet cross section as a function of rapidity y over the range 0≤|y|≤3 d0rapidity . This data set, comprised of 90 data points, has a greater statistical power in the global fits than the CDF and DØ jet cross section measurements in the central region alone. The CTEQ6M fit  cteq6 utilizes these DØ jet cross section measurements, along with the CDF measurements in the central rapidity region, as well as the most recent DIS data from HERA and existing fixed target DIS and DY data. An important step was taken to quantify the uncertainties of the parton distributions and their physical predictions with the inclusion of 40 eigenvector basis PDF sets, along with the best fit, to characterize the uncertainties in the neighborhood of the global minimum, using the Hessian method.
This paper is devoted to a detailed and more focused study of the uncertainties of the inclusive jet cross section due to global constraints, both at current energies, and more importantly for further QCD studies and the search for new physics at future collider programs. During the course of this work, we have produced an improved version of the CTEQ6 PDF's. The new minimum set, called CTEQ6.1M henceforth, provides a global fit that is almost equivalent in every respect to the published CTEQ6M cteq6 , although some parton distributions (e.g., the gluon) may deviate from CTEQ6M in some kinematic ranges by amounts that are well within the specified uncertainties. The more significant improvements are associated with some of the 40 eigenvector sets, which are made more symmetrical and reliable in CTEQ6.1M111The CTEQ6.1M parton distributions will be available in the CTEQ table format at www.phys.psu.edu/ cteq/ and in the LHAPDF format at vircol.fnal.gov.
The comparison between the DØ data for the 5 different rapidity intervals, and the predictions using the CTEQ6.1M PDF's, is shown in Fig. 1. The theory predictions for CTEQ6M, CTEQ5M and CTEQ5HJ parton distributions are also shown. The greater statistical power that results from including the new DØ jet data, and the fact that all of the rapidity intervals prefer a larger gluon at high x, results in the increases in the cross sections found using NLO predictions based on CTEQ6M or CTEQ6.1M rather than CTEQ5M.
Figure 1: The DØ inclusive jet cross section versus ET for five rapidity bins compared to NLO predictions using the CTEQ6.1M PDF's. The abscissa is ET in GeV. The ordinate is (data − theory)/theory. The curves show the CTEQ5M, CTEQ5HJ, and CTEQ6M predictions, as fractional differences compared to CTEQ6.1M. The error bars are the statistical and systematic errors combined in quadrature.
This point deserves further emphasis. It is crucial to measure the jet cross section over a wide rapidity range: any new physics should contribute mostly to the central rapidity region, while a PDF explanation will contribute to all rapidity ranges. This will be addressed in more detail below.
As discussed in Ref. cteq6 , it is important to have a parameterization for the PDF's that is flexible enough to allow an increase in the high x gluon, without modifying too much the shape of the gluon distribution at lower values of x. A comparison of the CTEQ5M, CTEQ5HJ and CTEQ6M gluon distributions is shown in Fig. 2. As can be observed, the CTEQ6M gluon at high x lies between the gluons in CTEQ5M and in CTEQ5HJ, just as the CTEQ6M predictions for the inclusive jet cross sections at high ET lie between the predictions using the two other PDF's. The CTEQ6.1M gluon distribution is shown by dashed curves in Fig. 2. At the highest x values the function resembles CTEQ5HJ, and in the intermediate x range it resembles CTEQ6M.
Figure 2: Left: The CTEQ5M, CTEQ5HJ, and CTEQ6M gluon distributions at Q2=10 GeV2. Right: The ratios of CTEQ5M and CTEQ5HJ gluon distribution to that of CTEQ6M. The dashed curves show the CTEQ6.1M gluon distribution.
The subprocess contributions to jet production are shown in the next figures, for the central rapidity bin (Fig. 3) and the forward rapidity bin (Fig. 4), for the parton distributions CTEQ5M and CTEQ6M.
The dominant difference between the CTEQ5M and CTEQ6M sets is the increased gluon distribution in CTEQ6M at large values of x; the quark distributions are nearly unchanged. This shows up as a decrease in the fractional contributions of the quark-quark subprocesses and as increases in the fractional contributions of the quark-gluon and gluon-gluon subprocesses. It is interesting to note that the gq scattering subprocess is even more important at high ET for the highest rapidity bin than for the central rapidity bin.
Figure 3: The subprocess contributions to central jet production.
Figure 4: The subprocess contributions to jet production in the forward rapidity region.
The cross section for production of high-ET jets at the Tevatron depends on the parton distributions at large x. The relevant range of x may be estimated by considering the leading-order 2→2 kinematics. Let x1 and x2 be the momentum fractions of the two incoming partons. The outgoing parton 4-momenta are
p′μ1 = (pTcoshy1,→pT,pTsinhy1), (1)
p′μ2 = (pTcoshy2,−→pT,pTsinhy2); (2)
the outgoing partons have rapidities y1 and y2, and transverse momenta →pT and −→pT, respectively. If the first parton is identified with the observed jet then the jet rapidity is yj=y1 and its transverse momentum is →pT. The 2→2 kinematics determines the relation between the momentum fractions and outgoing parton variables,
x1 = pT√s(eyj+ey2), (3)
x2 = pT√s(e−yj+e−y2). (4)
These parametric equations yield a curve in the (x1,x2) plane, parametrized by the rapidity y2 of the second parton, for the specified jet variables.
Figure 5 shows the (x1,x2) values for central rapidity (yj=0) on the left and forward rapidity (yj=2) on the right. In the central case, the solid curve is the locus of (x1,x2) points for pT=400 GeV and the dashed curve is for pT=200 GeV. Both x1 and x2 must be ≳0.25 to produce the high-pT jet. In the forward case the solid curve corresponds to pT=200 GeV and the dashed curve to pT=100 GeV. Here one parton must have large momentum fraction to produce the jet at large pT and forward rapidity. The second parton can have a low value of x, leading to the second jet being close in rapidity to the first jet, or a larger value of x, leading to configurations where the two jets are on opposite sides of the detector. Consider the contribution of the quark-gluon scattering subprocesses. For the configuration where one x is small and the other is large, the smaller x value most likely corresponds to a gluon and the larger to a quark. In this case the difference between the CTEQ5M and CTEQ6M distributions is small. On the other hand, for the configuration where both x values are large the increased gluon in CTEQ6M will enhance the cross section. The conclusion is that the increase in the cross section when going from CTEQ5M to CTEQ6M occurs in configurations where the forward jet is balanced in pT by a jet with roughly the opposite rapidity.
Next, consider the question of where in the jet phase space one is most likely to observe signs of compositeness or other new physics. The angular distributions of the dominant QCD subprocesses are sharply peaked at small scattering angles, whereas the models usually used to estimate compositeness have much flatter distributions. This means that the signal/QCD ratio will be largest for 90∘ scattering in the parton-parton rest frame. In the overall hadron-hadron frame, this corresponds both jets having the same rapidity. Using the lowest order kinematics described previously, the squared dijet mass is given by
M2jj=2p2T[1+cosh(y1−y2)].
Setting y1=y2 yields M2jj=4p2T. This shows that maximizing the dijet mass means maximizing pT. Since the pT reach is maximized in the central region, this is the region where the highest dijet masses can be reached with the lowest background for new physics signals (at least those with a flat angular distribution). The model discussed for compositeness later in this paper gives an explicit example of this behavior. On the other hand, as shown by the kinematic examples in Figs. 5, modifications of the gluon distribution at high values of x will affect the high-pT jet cross section at all rapidities.
Figure 5: Left: Parton momentum fractions x1 and x2 for yj=0; the solid and dashed curves are for ET=400 and 200 GeV, respectively. Right: Parton momentum fractions x1 and x2 for yj=2; the solid and dashed curves are for ET=200 and 100 GeV, respectively.
As discussed in the previous section, the cross section for inclusive jet production has been measured by the CDF and DØ collaborations at the Tevatron. These results have been used in the latest CTEQ global analysis of PDF's, leading to the CTEQ6 (and now 6.1M) parton distributions. In this section we analyze the uncertainty of the theoretical QCD cross section due to PDF uncertainty.
The Hessian method of uncertainty analysis has been described in detail previously PSTHessian . For completeness, we summarize the method briefly. The parton distributions are constructed by a method of chi-square minimization with fitting of systematic errors. A chi-square function χ′2 is defined by
χ′2 = ∑eχ2e(a,r) (5)
χ2e(a,r) = ∑i[Di−∑krkβki−Ti(a)]2α2i+∑kr2k (6)
where e labels an experimental data set and i labels a data point in the data set. Di is the data value, αi is the uncorrelated error, and βki is the kth correlated systematic error; these numbers are published by the experimental collaboration. Then Ti(a) is the theoretical value, a function of a set of n PDF parameters, {a1,…,an}. Also, {rk} is a set of Gaussian random variables and rkβki is a (correlated) shift applied to Di to represent the kth systematic error. We minimize the function χ′2(a,r) with respect to both the PDF parameters {a} and the systematic shift variables {rk}. The result yields both the standard PDF model with parameters {a0}, and the optimal shifts {ˆrk} to bring theory and data into agreement. This minimum of χ′2 represents the best fit to the data cteq6 .
The Hessian matrix is
Hij=12∂2ˆχ2∂ai∂ajwhereˆχ2(a)≡χ′2(a,ˆr(a)). (7)
This matrix determines the behavior of ˆχ2(a) in the neighborhood of the minimum. We have developed an iterative method for calculating the Hessian accurately, leading to an improvement in the χ2 minimization PSTIterative . The point {a0} in the n-dimensional parameter space—where ˆχ2(a) is minimum—is the best fit to the global data set. However, points in some small neighborhood of {a0} are also acceptable fits. The variation within the acceptable neighborhood, of a PDF or a physical prediction, is our measure of the uncertainty of the quantity.
In the Hessian method of uncertainty analysis, we first define n special directions in the parameter space, namely the n eigenvectors of the Hessian. Then for each eigenvector we have two displacements from {a0} (in the + and − directions along the vector) denoted {a+i} and {a−i} for the ith eigenvector. At these points, ˆχ2=ˆχ20+T2 where ˆχ20=ˆχ2(a0) = the minimum, and T is a parameter called the tolerance. We consider any PDF set with ˆχ2−ˆχ20<T2 to be an acceptable fit to the global data set. In particular, the 2n PDF sets {a±i}, which are called the eigenvector basis sets, span the parameter space in the neighborhood of the minimum.
The appropriate choice of tolerance T cannot be decided without a further, more detailed, analysis of the quality of the global fits. After studying a number of examples PSTHessian ; PSTLagrange we conclude that a rather large tolerance, T∼10, represents a realistic estimate of the PDF uncertainty.222Different choices of the tolerance have been made by other groups, e.g., T∼√40 by MRST mrst2002 .
Any quantity X that depends on PDF's has a predicted value X0=X(a0) and a range of uncertainty δX. A simple measure of δX is the spread of the values of X(a±i) for the 2n eigenvector basis sets. However, a more complete uncertainty range is between the minimum and maximum values of X for all points with ˆχ2−ˆχ20<T2. It can be shown that in a linear approximation these bounds are X0±δX where
(δX)2=T2∑i,j(H−1)ij∂X∂ai∂X∂aj; (8)
or, in terms of the eigenvector basis sets,
(δX)2=14n∑k=1[X(a+i)−X(a−i)]2. (9)
We refer to (9) as the Master Equation for the uncertainty of X in the Hessian method PSTHessian . Equation (9) is based on a linear approximation: ˆχ2(a) is assumed to be a quadratic function of the parameters {a}, and X(a) is assumed to be linear. We find that these approximations are not strictly valid, so instead we calculate asymmetric bounds by
δX±=n∑k=1[X(a±i)−X(a0)]2; (10)
the range of uncertainty of X is (X0−δX−,X0+δX+). (In (10) {a+i} and {a−i} are the displaced points where X>X0 and X<X0, respectively.)
The uncertainties on the gluon and u-quark distributions are shown in Fig. 6, for Q2=10 GeV2. The u-quark distribution is tightly constrained for x≲0.8, whereas the uncertainty on the gluon distribution grows to a factor of 2 or larger for x values greater than ∼0.4. For comparison, the CTEQ5M, CTEQ5HJ, MRST2001 mrst2001 and MRST2002 mrst2002 PDF's are shown, compared to CTEQ6.1M, in Fig. 7, for Q2=10 GeV2.
Figure 6: PDF uncertainties. The curves are the ratios of the 40 eigenvector basis sets to the standard set (CTEQ6.1M). The largest variations of the gluon function are the + and − displacements along eigenvector 15.
Figure 7: Comparison of several standard PDF sets.
To illustrate our method, and the importance of the systematic errors, Fig. 8 shows the fractional difference between the data obtained by CDF in Run 1b, and the theory with CTEQ6.1M partons. The error bars are the statistical errors only. The left panel is (Di−Ti)/Ti. Note that there are some systematic differences between the CDF jet data and the theory, both in terms of normalization and in shape.333It is important to note all Run 1 CDF cross sections are intrinsically larger than comparable DØ cross sections by approximately 6% due to different assumptions regarding the total inelastic cross section at 1.8 TeV cdf_d0_sigma . The right panel shows (¯¯¯¯¯Di−Ti)/Ti where ¯¯¯¯¯Di is the shifted data,
¯¯¯¯¯Di=Di−n∑k=1ˆrkβki; (11)
i.e., the optimal systematic shifts determined by the global fit have been subtracted from the data values. There is no systematic difference between ¯¯¯¯¯Di and Ti, as expected. The sizes of the systematic shifts are, as expected, comparable to the standard deviations published by the CDF collaboration; that is, ˆrk is of order 1 for each of the systematic errors.
Figure 8: The left panel shows (Di−Ti)/Ti, the fractional difference between data and theory. The right panel shows (¯¯¯¯¯Di−Ti)/Ti where ¯¯¯¯¯Di is the data with systematic shifts subtracted. The error bars are the statistical errors only.
Figure 9 shows the cross section for inclusive jet production at the Tevatron, integrated over the rapidity range 0.1<|η|<0.7, as a function of jet transverse energy ET, for CTEQ6.1M partons and for the 40 eigenvector sets. (The rapidity interval is that for which the cross section has been published by the CDF collaboration.) The spread of the 41 curves in Fig. 9 is a simple estimate of the PDF uncertainty. The CDF data points are superimposed on the calculation.
Figure 9: Calculations of dσ/dET for the 40 eigenvector sets.
Figure 10 shows the fractional differences [T(a±i)−T(a0)]/T(a0) between the 40 sets and the standard prediction (CTEQ6.1M). The points are the CDF data compared to CTEQ6.1M; the error bars are statistical errors and the data points are plotted without the systematic shifts. Also shown is the prediction using CTEQ5HJ partons. The range of uncertainty encompasses both the CDF data and the CTEQ5HJ predictions.
Figure 10: Calculations for the 40 eigenvector basis sets, plotted as fractional differences compared to CTEQ6.1M. The points are the CDF measurements. The error bars are statistical errors only; the systematic shifts are not subtracted from the data. The dashed curve is CTEQ5HJ compared to CTEQ6.1M.
Figure 11 shows the 40 eigenvector basis sets separately. For each eigenvector the two curves are the positive and negative displacements. The Hessian method assumes that the variations are approximately linear. If the linear approximation were strictly valid the curves would be mirror images about zero. Figure 11 implies that the linear approximation is reasonably accurate for most eigenvectors, especially those corresponding to the ten largest eigenvalues (1 – 10).
Figure 11: The cross sections for + and − displacements along the 20 eigenvectors, plotted as fractional differences compared to CTEQ6.1M.
Figure 12 shows the overall PDF uncertainty calculated from the "Master Equation," asymmetrically for positive and negative differences. The ordinate is the fractional difference between the extreme cross section and the central (CTEQ6.1M) prediction. The outer curves are the upper and lower bounds of the uncertainty band. The CDF data is superimposed.
Figure 12: The overall PDF uncertainty of the inclusive jet cross section is plotted as the two red curves. The points are CDF data; the error bars are statistical only and the systematic shifts have not been subtracted.
The overall uncertainty in the calculation of (dσ/dET)CDF is dominated by one of the eigenvector directions. The dominant eigenvector is "eigenvector 15," i.e., that for which the eigenvalue of the Hessian is 15th in order of magnitude. The + and − displacements in parameter space along this direction have a much larger effect on the value of the cross section than any of the other eigenvector directions. In other words, (dσ/dET)CDF is most sensitive to the parameter variations along this eigenvector. Figure 13 shows the gluon distribution for CTEQ6.1M and for the eigenvector basis sets in the + and − directions along eigenvector 15. Eigenvector 15, like the 19 others, corresponds to some linear combination of all of the 20 fitting parameters. The exceptional feature of eigenvector 15 is that it represents the largest change in the high-x gluon behavior.
Figure 13: Eigenvector 15. Comparison between the gluon distributions for the + and − displacements along eignevector 15 and the standard set CTEQ6.1M.
In the new CTEQ6.1M analysis, the eigenvector basis sets have been carefully constructed to have ˆχ2=ˆχ20+100.444The earlier CTEQ6 analysis cteq6 made an approximation of the NLO cross sections—holding the K-factor tables for DIS and DY processes constant as the PDF parameters varied in the neighborhood of the minimum—such that Δˆχ2 was not strictly constant at T2 for the Hessian PDF sets. The CTEQ6.1M analysis is preferred although the changes from CTEQ6 are small. But ˆχ2 is the global chi-square function. The criterion Δˆχ2=100 is only a reasonable rule of thumb, and a more thorough analysis—inspecting the fit for each data set—is needed to justify the extreme sets a+15 and a−15. We must ask whether these variations could be ruled out by any specific experiment.
The theoretical cross section most affected by displacements along eigenvector 15 is the inclusive jet cross section. Table 1 shows the ˆχ2 values for the CDF and DØ data for three PDF sets (a0, a+15 and a−15.) Because of the significant systematic uncertainties in the experimental data, represented by the error correlation matrices published by the collaborations, we might conclude that the extreme sets a+15 and a−15 are still acceptable fits to the data within the systematic errors.
PDF set
DØ χ2
DØ χ2/N
CDF χ2
CDF χ2/N
(N=90)
CTEQ6.1M 52.26 0.581 57.67 1.748
EV set 15+ 111.90 1.243 53.05 1.608
EV set 15− 39.17 0.435 67.35 2.041
Table 1: χ2/N for the standard PDF's (CTEQ6.1M) and the extreme variations in the + and − directions along eigenvector 15.
As implied by the table above, much of the increase in χ2 (50 out of 100) for eigenvector +15 comes from the DØ jet cross section. The Run 1b DØ cross section can tolerate some increase compared to the CTEQ6.1M predictions, but the increase corresponding to eigenvector +15 is in fact too extreme. It is not surprising that such a large portion of the increase in χ2 comes from the DØ jet data: as shown in Fig. 13, this eigenvector probes primarily the high-x gluon distribution and the other data sets (with the exception of the CDF jet data) are fairly insensitive to this direction. The opposite direction, eigenvector −15, gives the lowest χ2 for the DØ jet data. (Of course the χ2's of other experiments are larger so that the net change is 100.) The cross section in this case is less than that for CTEQ6.1M, by as much as 10 – 20%. The fact that ˆχ2/N is much less than 1 for the DØ data suggests that the size and correlation of systematic errors are not accurately understood and thus CTEQ6.1M gives a satisfactory fit although not the best fit.
Figures for the DØ jet data analogous to Figs. 9 and 10 are shown in Figs. 14 and 15. Figure 14 shows the inclusive jet cross section as a function of ET for the five rapidity bins of the DØ measurements. Calculations for all 40 eigenvector basis sets are superimposed. The points are the DØ data and the error bars equal the single-point statistical and systematic errors added in quadrature.555The systematic errors for the DØ data are supplied by the collaboration only in the form of correlation matrices. Unlike the CDF data, for which the standard deviations of individual systematic errors have been published, we are unable to separate the optimal systematic shifts for subtraction from the DØ data. Figure 15 shows the inclusive jet cross section as a function of ET for the five rapidity bins, plotted as fractional differences compared to the central (CTEQ6.1M) model.
Figure 14: The inclusive jet cross section as a function of ET for the five rapidity bins of the Run 1b DØ measurements. Predictions of all 40 eigenvector basis sets are superimposed. The points are the DØ data, and the error bars are the statistical and systematic errors combined in quadrature.
Figure 15: The DØ inclusive jet cross section as a function of ET for five rapidity bins, plotted as fractional differences compared to the central (CTEQ6.1M) model. The abscissa is ET in GeV and the ordinate is [T(a)−T(a0)]/T(a0) for the curves and (D−T)/T for the points.
Thus far, the discussion of uncertainties has dealt primarily with the issue of the propagation of experimental errors on the observables and their effect on the parameters of the parton distributions. There are, of course, issues related to theoretical uncertainties both in the global fit itself and in the theoretical calculations for jet production. However, it is far more difficult to quantify these. We have previously described studies of some theoretical uncertainties cteq6 . For example, we have chosen cuts on Q and W for the DIS data sets used for CTEQ6 and earlier analyses in order to reduce the theoretical uncertainties due to effects from higher twist and related terms. Also, we have varied the functional form of the parametrization to ensure that sufficient flexibility to cover the wide kinematic range of x and Q is available. In this section we concentrate on the theoretical uncertainties related to NLO calculations for jet production. The response of the predictions to variations in the renormalization and factorizations scales yields some information on the theoretical uncertainties. In this section the scale dependence of the jet cross sections and the effects on the fits of varying the scales will be discussed. Some estimates of the possible effects of two-loop corrections will also be presented.
Figure 16: Comparison of the scale dependence of the jet cross section at ET=70 GeV/c for the leading- and next-to-leading-logarithm calculations
Figure 17: Comparison of the scale dependence of the jet cross section at ET=170 GeV/c for the leading- and next-to-leading-logarithm calculations
Leading-logarithm calculations of the jet cross section at high-ET generally decrease monotonically as the factorization and renormalization scales are increased. The scale variation of next-to-leading-logarithm calculations is generally reduced as compared to that of the leading-log calculations. A brief review of how this comes about is presented in the Appendix.
The increased rapidity coverage available with the recent DØ data d01b has provided additional constraints on the gluon distribution. However, if the theoretical uncertainties become large at high rapidity, then these constraints may not be as useful as first believed. As one approaches the edge of phase space, it might be anticipated that there will be large logarithms due to the constraints on multiple gluon emission. The effects of these large logs will be investigated in Sec. (III.3). Their effects may show up already in the next-to-leading-log calculations used in the global fits, so it is important to look for any anomalous behavior in the predictions.
The first step is to examine the scale dependence of the jet cross section predictions in the highest rapidity bin of the DØ data. For ease of presentation, the factorization and renormalization scales have been chosen to be the same. In the jet cross section calculations used for the CTEQ PDF fits, and in this paper, a scale μR=μF=ET/2 has been used. Fig. 16 shows the comparison of the scale dependences of the leading-log and next-to-leading-log calculations at ET=70 GeV/c. The monotonically decreasing behavior of the leading-log results is evident, as is the roughly quadratic dependence of the next-to-leading-log curve. Both behaviors are consistent with the expectations discussed in the Appendix. Similar results are shown in Fig. 17 for ET=170 GeV/c. Both figures show that the scale dependence of the next-to-leading-log calculation is greatly reduced with respect to that of the leading-log calculation, provided that one avoids scale choices much smaller that μ=ET.
It is interesting to note that the K-factor (NLO/LO) for μ=ET/2 is approximately unity for ET=70 GeV/c, while it is significantly less for ET=170 GeV/c. The reasons for this are discussed in more detail in Appendix A.
The next point to be addressed is the effect on the fits of varying the choice of scale. To investigate this point, the CTEQ6M fits666This procedure has not been repeated with the CTEQ6.1M PDF's. However, since the changes in the region of the DØ and CDF data were minimal, the scale dependence in the 6M and 6.1M sets should be essentially the same. were repeated with scale choices of μ=ET and 2ET. As compared to the original fit with μ=ET/2 the latter two yielded increases in chi-square of 16 and 70, respectively. Thus, the choice of ET/2 used in the CTEQ6M fits yields the best chi-square of the three choices, but this does not constitute a fit for the optimal scale. Note, however, that the rapid increase in the scale dependence for choices below about ET/2 shown in Figs. 16 and 17 precludes fits with significantly smaller scales while the larger scale choices show an increase in chi-square.
The gluon distributions from these fits are shown in Fig. 18 relative to the standard CTEQ6M distribution corresponding to μ=ET/2. The effects at values of x below about 0.4 are minimal, but the effects at larger x values are significant. In particular, the reduction in the cross section due to the larger scale choice of 2ET is compensated by an increase of the gluon distribution. However, it should be noted that the chi-square increased by 70 units for this fit. This is still less than the chi-square increase of 100 that determines the 40 error PDF's.
A comparison of Fig. 18 to Fig. 6 indicates that the uncertainty on the gluon distribution due to the scale choice for jet production in the global fits is everywhere less than the uncertainty from the treatment of the experimental errors.
Figure 18: Comparison of fitted gluon distributions for fits made with different scale choices for the jet cross section. Comparison to Fig. 6 shows that this theoretical error is smaller than the uncertainty due to experimental errors.
It is important to bear in mind that the gluon distribution itself is not an observable quantity. Rather, the gluon and quark distributions contribute via convolutions with appropriate hard scattering cross sections. Accordingly, the impression provided by Fig. 18 may be somewhat misleading as much of the gluon variation is offset by changes in the hard scattering cross section with which it is convoluted, with the end result being that the variation in the physical observables is much less.
The jet cross section predictions using scales of ET/2, ET and 2ET are shown in Figs. 19 and 20 for the DØ rapidity regions of 0.0 – 0.5 and 2.0 – 3.0. These curves may be compared to those for bins 1 and 5 in Fig. 15. The scale dependence variations are generally within the bands formed by the 40 eigenvector basis sets, indicating that the uncertainty introduced by the scale dependence of the jet cross sections is less than or on the order of that coming from the experimental errors.
Figure 19: Scale dependence of the jet cross section prediction for 0<y<0.5.
Figure 20: Scale dependence of the jet cross section prediction for 2<y<3.
As noted in the introduction to this section, there are potentially significant contributions to the jet cross resulting from phase space limitations on gluon emission as one goes to large ET and large rapidity. Such corrections can be treated by threshold resummation techniques resum . In Ref.  twoloop these corrections for jet production were estimated at the two-loop level for central rapidity values and found to be small. The calculation has been repeated for the largest rapidity bin covered in the DØ data d01b and the results are shown in Figs. 21 and 22 by the dashed lines. As was the case in the central region, the two-loop estimates of the next-to-next-to-leading-logarithm contributions are not large for the scale choices considered in this analysis.
Figure 21: Same as Fig. 16 with the addition of the estimated two-loop contribution expected from threshold resummation.
Figure 22: Same as Fig. (17) with the addition of the estimated two-loop contribution expected from threshold resummation.
To summarize the results of this section, the next-to-leading-logarithm jet calculations show the expected reduction in scale dependence, even for large values of ET in the highest rapidity bin in the existing data set. Nevertheless, the remaining scale variation does show up in an increased uncertainty in the gluon distribution at large values of x. This uncertainty is, of course, partially offset by the compensating scale dependence of the hard scattering cross section. Even so, the scale dependence of the next-to-leading-log calculations remains as a contributing factor for the overall uncertainty of the predictions for new processes. Finally, the next-to-next-to-leading-log corrections estimated by expanding the threshold resummation predictions for jet production remain small, even at high ET in the highest rapidity bin considered, lending support to the use of the next-to-leading-log expressions in the global fit.
Hadron collider jet data have traditionally been used to constrain models of new physics, usually models of quark substructure. The measurements include dijet angular distributions that are insensitive to theoretical uncertainties due to parton distributions angdist . Inclusive jet cross sections or dijet mass distributions typically provide better probes of quark compositeness, but are sensitive to parton distributions at large x which have large uncertainties dijetmass . Currently the best limits are provided by a hybrid approach that uses the ratio of dijets in different rapidity bins d0dijet . This approach has the advantage that many theoretical and experimental systematic errors cancel out in the ratio. It has the disadvantage that it removes some useful information, such as the absolute values ot the cross sections in the two rapidity intervals.
There are several reasons to revisit this issue. First, the published limits are based on parton distributions several generations old, and the best-fit gluon distribution at large x is significantly changed. Second, the recent jet measurements at large rapidity provide constraints on the large x partons while being largely insensitive to new physics. Finally, and most important, the global analysis machinery has never been used in these analyses to refit the parton distributions in the presence of a new component to the QCD calculation. If the constraints on the parton distributions are not sufficient, it is possible that new physics could hide inside the PDF uncertainties, or current limits may be weakened.
Compositeness signals are typically parameterized by a mass scale Λ which characterizes the quark substructure coupling. The coupling is approximated by a four-Fermi contact interaction giving rise to an effective Lagrangian. Only the term describing left-handed coupling of quarks and anti-quarks has been calculated comp ,
Lqq=A(2π/Λ2)(¯¯¯qLγμqL)(¯¯¯qLγμqL)whereA=±1. (12)
The simplest squared amplitude is the quark anti-quark s-channel annihilation process, with the first term the normal QCD interaction and the second due to substructure:
∣A(u¯¯¯u→d¯¯¯d)∣2=49α2S(Q2)(ˆu2+ˆt2)ˆs2+AˆuΛ2. (13)
Since ˆu is negative, constructive (destructive) interference in this process occurs when A=−1 (+1). This is generally true for the other scattering terms as well, which will be included in the calculations. As in the experimental papers, we will use the quark compositeness implementation in PYTHIA pythia to form the ratio of QCD+substructure/QCD, then multiply this ratio by the NLO QCD calculation for each iteration of parton distribution as the PDF parameters are being fit. As expected, we find larger cross sections with the constructive interference choice A=−1, approximately a factor of 10 larger. However, the ratio of the first two eta bins used by DØ is slightly larger with the destructive interference term A=1, and this is what is used for the current best limit of Λ>2.7 TeV d0dijet . Therefore we have used the destructive interference choice for illustration in the rest of this paper.
Figure 23 shows the cross section for jet production including a contact interaction, for three values of Λ: 1.6, 2.0 and 2.4 TeV. The cross section is plotted as a ratio to the pure QCD prediction with the CTEQ6.1M parton distributions. The range of kinematic parameters are the same as the DØ data, and the DØ data is superimposed on the plots with error bars of statistical and systematic errors combined in quadrature.
If the effect of the contact interaction is smaller than the PDF uncertainty of the QCD prediction then the data cannot rule out the compositeness model; any difference between theory and data could be explained either as a PDF effect or as a sign of new physics. However, if the compositeness model disagrees with the data by an amount that is larger than the PDF uncertainty, the model is ruled out. The PDF uncertainty of the QCD prediction is comparable to the experimental error bars (see Fig. 15), so we may use those error bars to judge whether the effect of the contact interaction is smaller than the PDF uncertainty. The contact interaction is seen to be ruled out for Λ=1.6 TeV, primarily from the disagreement with the central rapidity interval, 0<η<0.5. The cross section at large rapidity (η>1.5) is not sensitive to the contact interaction.
The largest two Λ values, Λ=2.0,2.4 TeV, are not inconsistent with the DØ data on inclusive jet production because the effect of the contact interaction is within the PDF uncertainty. The global fit for Λ=2.4 TeV is even slightly better than for the pure QCD model, although the difference in the overall quality of the fit (Δχ2global=9) is much less than our standard tolerance for PDF uncertainty (Δχ2global≲100).
Figure 23: Comparison of three models in which a hypothetical contact interaction contributes to jet production. The ordinate is the fractional difference between the model and the standard theory; the abscissa is the jet ET in GeV. The contact interaction has Λ=1.6, 2.0, and 2.4 TeV for the three curves. In all cases the PDF's are the standard CTEQ6.1M. The DØ data are superimposed for comparison.
If there is a contact interaction, then the CTEQ6.1M PDF's would be inaccurate because the data were fit to a pure QCD model. Therefore a complete analysis of the contact interaction requires that the PDF's be refit, comparing the data to the theory with compositeness. Figure 24 shows the final result of this analysis. The cross section for jet production with the DØ kinematic parameters is again shown for three values of the Λ parameter (1.6, 2.0 and 2.4 TeV) as a ratio to the pure QCD model with CTEQ6.1M. In Fig. 24 the PDF's for each Λ value come from a global fit that includes the contact interaction in the theory of the jet cross section. The smallest value of Λ is now more consistent with the data, but still ruled out.
The limit derived from this analysis, Λ>1.6 TeV, is not as strong as those from either the CDF or DØ analyses that use angular distribution information angdist . This is a result of the remaining uncertainty in the PDFs, and the fact that in this model of new physics the angular distributions are quite different than QCD. Other deviations from the Standard Model might change the absolute cross sections while maintaining a more QCD-like angular distribution. In this case this analysis is the most in-depth study so far of allowed deviations in jet cross sections due to new physics.
The limit derived from this analysis is also less than that obtained by the DØ collaboration when using the ratio of the dijet cross sections in the two rapidity bins (0.0−0.5 and 0.5−1.0). However, it should be noted that at least part of the higher limit from DØ may be due to the dijet cross section for 0.5<η<1.0 being somewhat larger than the standard model prediction, while the dijet cross section for 0.0<η<0.5 is in better agreement with the SM prediction. The larger the ratio of the 0.5−1.0 to 0.0−0.5 rapidity intervals, the stronger the compositeness limit. The detailed information about the absolute values of the cross sections in each rapidity bin has not been used.
Figure 24: Comparison of three models in which a hypothetical contact interaction contributes to jet production, with refitting of the PDF's. The curves have the same meaning as in Fig. 23. The PDF's for the three models have been refit to the global data set to give the best fit including the contact interaction in jet production.
Table 2 shows how the χ2's are affected by the contact interaction.
Λ [TeV] PDF set global χ2 DØ χ2/N CDF χ2/N
1.6 CTEQ6.1M 2111 0.939 5.45
∞ CTEQ6.1M 1957 0.590 1.68
1.6 best refit 2079 1.230 3.63
Table 2: χ2's for three theoretical models with a contact interaction.
The increase in the center-of-mass energy (from 1.8 to 1.96 TeV) and the increased luminosity expected in Run 2 (from approximately 100 pb−1 to 2 – 15 fb−1 will result in a dramatically larger kinematic range for measuring jet production, and thus for searching for possible new physics as well. Also, in Run 2, the new CDF endplug calorimeter will allow for an extension of measurements of the inclusive jet cross section to the forward rapidity region, similar to the analysis that has been performed by DØ in Run 1b.
Figure 25: Run 2 cross section for the DØ rapidity bins. Left: The 40 eigenvector basis sets. Right: The central prediction and overall uncertainty band.
The predictions for the Run 2 jet cross section as a function of transverse momentum (using the DØ rapidity intervals) are shown in Fig. 25. With 2 fb−1 (Run 2a) a measurement of the inclusive jet cross section out to a transverse energy of 600 GeV is possible, while with 15 fb−1 (Run 2b) the measurement can be extended to almost 650 GeV. The predictions are displayed on the left graph in the form of the curves for the 40 eigenvector basis sets of CTEQ6.1M. The central prediction and overall uncertainty band from the Master Equation (10) are shown separately on the right graph. Figure 26 shows the uncertainty range of the Run 2 cross section by displaying the ratios of the eigenvector basis sets to the central prediction. Near the kinematic limit, the PDF uncertainties allow the cross section predictions to be as much as a factor of 2 larger than those from the central fit (CTEQ6.1M), again due to eigenvector 15.
Figure 26: Uncertainty range of the Run 2 cross section for the DØ rapidity bins. The curves show the ratios of the 40 eigenvector basis sets to the central (CTEQ6.1M) prediction (ordinate) versus pT in GeV (abscissa).
For the Run 2 jet cross section predictions, we have used the Run 2 cone jet algorithm run2work ; ellis which uses 4-vector kinematics both to define the jet and to specify its transverse momentum and rapidity. This algorithm has been adopted by both the CDF and DØ collaborations for their inclusive Run 2 jet results. Note that this algorithm specifies the transverse momentum pT rather than the transverse energy ET.777The Run 2 jet algorithm results in cross section predictions for CDF that are ∼7% lower than those using the Run 1 algorithm, over most of the kinematic range.
For completeness we also show the plots of the predictions of the inclusive jet cross section at the Tevatron Run 2 for the CDF choice of rapidity bins. Figure 27 shows the cross section as a function of pT on a log scale. Figure 28 shows the uncertainty band in the form of the ratios of dσ/dpT for the 40 eigenvector basis sets compared to the central prediction.
Figure 27: Run 2 cross section for the CDF rapidity bins.
Figure 28: Uncertainty range of the Run 2 cross section for the CDF rapidity bins. The curves show the ratios of the 40 eigenvector basis sets compared to the central (CTEQ6.1M) prediction (ordinate) versus pT in GeV (abscissa).
While the statistical errors in Runs 2a and 2b will be small, so that the jet cross section can be extended to high pT, the experience from Run 1b shows that the systematic errors will have a dominant effect on the significance of the results. However, we can anticipate that the PDF's, especially the gluon distribution, will be pinned down at large x by these data. The experimental collaborations will make the data most useful for global analysis by providing detailed information on systematic uncertainties.
As mentioned previously, the Run 2 center-of-mass energy √s is higher than that from Run 1b. The increase in √s will have only a modest impact on most physics cross sections. However, it will lead to a rather large increase in the production of high-ET jets. It may be useful to examine the ratio of jet production (for the same ET values) at the two different energies. In such a ratio, many of the theoretical (and experimental) errors will cancel. The Run 2 to Run 1b ratio for the 40 sets of PDF's is shown in Fig. 29 for the central rapidity range of CDF (0.1<|η|<0.7). As can be observed the ratio has a rather narrow theoretical error band from PDF uncertainties, i.e., smaller uncertainty than that of the absolute prediction of the inclusive cross section.888Here we have multiplied our Run 2 predictions by a factor of 1.07 so that the comparison effectively uses the Run 1 algorithm for both the numerator and denominator. This is done for convenience since CDF will present its first results for the Run 2 jet cross section using the Run 1 algorithm.
Figure 29: The ratio of the Run 2 to Run 1b cross sections for the central rapidity range (0.1<|η|<0.7). The Run 2 cross section has been multiplied by 1.07 to take into account the difference in the jet definitions for the Run 2 and Run 1b analyses. (The small fluctuations are due to the Monte Carlo errors in the calculations of the K-factors (NLO/LO) at each energy.)
The increase of the center-of-mass energy to 14 TeV at the LHC will result in a dramatically larger accessible kinematic range. Inclusive jet cross sections will be measured out to transverse momentum of 5 TeV/c in the central rapidity range and out to 1.5 TeV/c in the forward rapidity region. Figure 30 shows the predictions with uncertainty ranges for three rapidity intervals. Figure 31 shows the ratios of the 40 eigenvector basis set predictions to the central prediction. The cross section uncertainties near the kinematic limit at the LHC due to PDF uncertainties are similar in magnitude to those obtained for Run 2 at the Tevatron. Again the extremes of the predictions are provided by the eigenvector basis sets +15 and −15, which correspond to extremes of the gluon distribution at large x.
Figure 30: The inclusive jet cross section as a function of pT for three rapidity bins at the LHC. The three rapidity ranges are (0,1), (1,2) and (2,3). Predictions of all 40 eigenvector basis sets are superimposed.
Figure 31: The uncertainty range of the inclusive jet cross section at the LHC. The curves are graphs of the ratios of the cross sections for the 40 eigenvector basis sets compared to the central (CTEQ6.1M) prediction (ordinate) versus pT in GeV (ordinate).
The jet cross section at the LHC will be a discovery mode for new physics. Supersymmetry would produce an enhanced cross section from production of gluino and squark jets. Extra dimensions would show up from production of Kaluza-Klein modes of the graviton. So the pure QCD prediction will be compared to the data and any difference will be the first evidence for these or other new physics scenarios.
Jet production serves as a probe of the highest Q2 scales accessible at a hadron-hadron collider. NLO QCD provides a good description of the inclusive jet cross sections measured by CDF and D0 in Run 1 at the Tevatron, provided that the gluon distribution is enhanced at high x relative to earlier estimates. Such an outcome is now the standard consequence of the global fitting procedure due to the statistical power of the Tevatron jet data, and the preference for a larger gluon in all rapidity regions. The uncertainties on the jet cross section predictions still remain large, however, primarily due to the remaining uncertainties on the gluon distribution. In most regions, they are comparable to the experimental systematic uncertainties.
The standard choice for the renormalization and factorization scales in evaluating inclusive jet cross sections has been EjetT/2. We have re-done the global fitting using alternate scales of EjetT and 2EjetT and have found changes to the gluon distribution that are well within the gluon PDF uncertainty band. The effects of the resummation of threshold logarithms has been calculated for the first time in the forward rapidity regions. As for the central rapidity region, the effects of the threshold logarithms are relatively small.
The increase of the center-of-mass energy to 1.96 TeV (from 1.8 TeV) and the expected greater integrated luminosity will lead to an expanded kinematic range for Run 2 at the Tevatron. Predictions have been made for both the inclusive jet cross section and its uncertainty for Run 2 and for the LHC. The PDF uncertainty on the jet cross section near the limits of the data reach in both cases are similar to those obtained for Run 1.
We have carried out an exercise where we have examined the allowed range for any new physics such as compositeness, given the current scale of uncertainties on the jet cross section predictions. Given the Run 1b jet data, any new physics must have a scale larger than 1.6 TeV. When data is available from Run 2 at the Tevatron, and from the LHC, analogous analyses will be used to identify evidence for new physics or place even stricter limits on new physics.
One component of the theoretical uncertainty of any perturbative QCD calculation is the dependence of the answer on the various renormalization and factorization scales. One virtue of using NLO calculations in global determinations of parton distributions is the reduction in scale dependence usually exhibited by such calculations. The following brief discussion outlines the origin of the reduction of the scale dependence which is often observed with NLO calculations.
Consider a large transverse momentum process such as the single jet inclusive cross section involving only massless partons. Furthermore, in order to simplify the notation, suppose that the transverse momentum is sufficiently large that only the quark distributions need be considered. In the following, a sum over quark flavors is implied. Schematically, one can write the lowest order cross section as
Ed3σdp3≡σ=a2(μ)^σB⊗q(M)⊗q(M) (14)
where a(μ)=αs(μ)/2π and the lowest order parton-parton scattering cross section is denoted by ^σB. The renormalization and factorization scales are denoted by μ and M, respectively. In addition, various overall factors have been absorbed into the definition of ^σB. The symbol ⊗ denotes a convolution defined as
f⊗g=∫1xdyyf(xy)g(y). (15)
When one calculates the O(α3s) contributions to the inclusive cross section, the result can be written as
σ = a2(μ)^σB⊗q(M)⊗q(M) (16)
+ 2a3(μ)bln(μ/pT)^σB⊗q(M)⊗q(M)
+ 2a3(μ)ln(pT/M)Pqq⊗^σB⊗q(M)⊗q(M)
+ a3(μ)K⊗q(M)⊗q(M).
In writing Eq. (16), specific logarithms associated with the running coupling and the scale dependence of the parton distributions have been explicitly displayed; the remaining higher order corrections have been collected in the function K in the last line of Eq. (16). The μ dependence of the running coupling is obtained from
μ∂a(μ)∂μ=β(a(μ)) (17)
where β=−ba2(1+ca) with
b=33−2f6 and c=153−19f2(33−2f) (18)
where f denotes the number of flavors. The scale dependence of the quark distributions is given by the nonsinglet DGLAP equation DGLAP
M∂q(x,M)∂M=a(M)Pqq⊗q(M). (19)
Now, the NLO expression in Eq. (16) should be independent of the choice of scale up to corrections of order a4. That this is indeed the case is easy to see. For convenience, set M=μ and calculate the logarithmic derivative of σ with respect to μ,
μ∂σ∂μ= 2a(μ)[−ba2(μ)(1+ca(μ))]^σ⊗q(μ)⊗q(μ)
+2a3(μ)Pqq⊗^σB⊗q(μ)⊗q(μ)
+2ba3(μ)^σB⊗q(μ)⊗q(μ)
−2a3(μ)Pqq⊗^σB⊗q(μ)⊗q(μ)+⋯
=0+O(a4). (21)
The derivative of the lowest order contribution yields the first two lines of Eq. (21) while the derivative of the logarithms in the second and third lines of Eq. (16) give rise to the last two lines in Eq. (21) which cancel the μ dependent terms coming from the derivative of the lowest-order contribution. All other derivatives yield contributions which are of order a4. Thus, the structure of the NLO calculation is such that the scale dependence is cancelled up to terms of order a4.
The preceding discussion shows that one might expect a reduced scale dependence for the NLO calculation as opposed to that observed at lowest order. However, the uncancelled O(a4) and higher terms will still result in some scale dependence. It is easy to understand the systematics of the remaining dependence for the case at hand. Consider, first, the lowest-order contribution shown in the first line of Eq. (16). At large values of pT as xT=2pT/√s tends to one, the scaling violations of the parton distributions lead to a decrease in the cross section as the scale increases. In addition, the running coupling decreases as the scale is increased. Therefore, at fixed pT the lowest order contribution exhibits a monotonically decreasing behavior as the scale increases.
The second line of Eq. (16) contains the contribution which partially offsets the scale dependence of the running coupling. Apart from the explicit logarithm, this contribution has much the same scale dependence as the lowest order contribution. Thus, for μ<pT this term is negative, becoming positive as the scale is increased beyond pT.
The third line contains the contribution which partially offsets the scale dependence originating in the parton distributions. In the kinematic region under consideration, the convolution of the splitting function Pqq with the lowest contribution gives a negative result, reflecting the fact that the parton distributions decrease with increasing scale at large values of x. Therefore, this contribution is negative when the factorization scale M is chosen to be less than pT.
Finally, the remaining term on line four of Eq. (16) has much the same scale dependence as the lowest order term, as the dominant scale dependence has already been exhibited in the terms on lines two and three. Thus, lines one and four give contributions which decrease monotonically with increasing scale while lines two and three start out negative, reach zero when the scales are equal to pT, and are positive for larger scales. This behavior explains why the typical NLO scale dependence in the high-pT region yields a result which first increases with increasing scale, reaches a maximum, and then decreases. For many high-pT processes involving massless partons this maximum occurs near μ=M=pT.
Next, it is interesting to consider how the location of the maximum changes with pT. Suppose that one goes to small values of xT such that the typical values of x in the parton distributions is around .2 or smaller. In this region the scaling violations change sign, corresponding to a growth of the parton distributions with increasing scale, rather than a decrease. The contribution of the third line of Eq.(1) then starts to compete against that of the second line. Accordingly, one must go to smaller values of μ/pT before seeing the turnover and decrease with decreasing scale. That is, the position of the maximum at fixed pT moves to lower values of μ/pT as pT decreases. The converse is also clearly true; as pT increases the position of the maximum moves to higher values of μ/pT. Thus, if one were to try to find an optimized scale at each value of pT, the pattern that would emerge would be that the optimal scale would be a fractional multiple of pT at lower pT values and would increase to a multiple of pT greater than one at higher pT values. This pattern is precisely what is observed when using the single scale version of the Principle of Minimal Sensitivity PMS .
Another manifestation of this pattern concerns the behavior of the "K factor", defined as the ratio of the NLO to LO result. At a fixed value of pT, the K factor will first rise and then fall with increasing scale. Suppose that at some pT value the maximum occurs for the choice μ=M=pT/2. Then, as one goes to higher pT values the previous discussion shows that the maximum will move to a higher scale choice such as pT or even 2pT. At the larger pT values it will then appear that the K factor may increase with increasing scale. This is just the behavior seen in the calculations done for the high rapidity D0 jet data.
(1) F. Abe, et al., (CDF Collaboration) Phys. Rev. Lett. 77, 438 (1996).
(2) J. Huston, E. Kovacs, S. Kuhlmann, H.L. Lai, J.F. Owens, D. Soper, W.K. Tung, Phys.Rev.Lett. 77, 444 (1996).
(3) H.L. Lai, J. Huston, S. Kuhlmann, F. Olness, J.F. Owens, D. Soper, W.K. Tung, H. Weerts, Phys.Rev. D55, 1280 (1997).
(4) H.L. Lai, J. Botts, J. Huston, J.G. Morfin, J.F. Owen, J.W. Qiu, W.K. Tung, H. Weerts, Eur.Phys.J. C12, 375 (2000).
(5) T. Affolder, et al. (CDF Collaboration), Phys.Rev. D64, 032001 (2001); Erratum-ibid. D65, 039903 (2002).
(6) B. Abbott, et al. (D0 Collaboration), Phys.Rev.Lett. 82 2451 (1999).
(7) B. Abbott, et al., (D0 collaboration) Phys.Rev. D64, 032003 (2001)
(8) J. Pumplin, D.R. Stump, J. Huston, H.L. Lai, P. Nadolsky, W.K. Tung, JHEP 0207, 012 (2002).
(9) A.D. Martin, R.G. Roberts, W.J. Stirling, R.S. Thorne, Eur.Phys.J. C23 73 (2002).
(10) A.D. Martin, R.G. Roberts, W.J. Stirling, R.S. Thorne, hep-ph/0211080.
(11) J.E. Huth, et al., in Proceedings of Research Directions for the Decade: Snowmass 1990, edited by E.L. Berger (World Scientific, Singapore, 1992).
(12) J. Pumplin, D.R. Stump, W.K. Tung, Phys.Rev. D65, 014011 (2002).
(13) J. Pumplin, D. Stump, R. Brock, D. Casey, J. Huston, J. Kalk, H.L. Lai, W.K. Tung, Phys.Rev. D65, 014013 (2002).
(14) D. Stump, J. Pumplin, R. Brock, D. Casey, J. Huston, J. Kalk, H.L. Lai, W.K. Tung, Phys.Rev. D65, 014012 (2002).
(15) G.C. Blazey and B.L. Flaugher, Ann. Rev. Nucl. Part. Sci. 49 633 (1999).
(16) N. Kidonakis, G. Oderda, and G. Sterman, Nucl. Phys. B525, 299 (1998); Nucl. Phys. B531, 365 (1998).
(17) N. Kidonakis and J.F. Owens, Phys. Rev. D63, 054019 (2001).
(18) B. Abbott, et al., (DØ Collaboration) Phys. Rev. Lett. 80, 666 (1998); F. Abe, et al., (CDF Collaboration) Phys. Rev. Lett. 77, 5336 (1996); Erratum-ibid. 78, 4307 (1997).
(19) B. Abbott, et al., (DØ Collaboration) Phys.Rev.Lett. 82, 2457 (1999).
(20) B. Abbott, et al., (DØ Collaboration) Phys. Rev. Lett. 82, 2547 (1999).
(21) E. Eichten, K. Lane, and M. Peskin, Phys. Rev. Lett. 50, 811 (1983).
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(25) See, for example, a detailed discussion in S. Ellis, J. Huston and M. Tonnesmann, Bulding Better Cone Jet Algorithms, in preparation.
(26) G.C. Blazey, J.R. Dittmann, S.D. Ellis, V.D. Elvira, K. Frame, S. Grinstein, R. Hirosky, P. Piegaia, H. Schellman, R. Snihur, V. Sorin, and D. Zeppenfeld, Run II Jet Physics, in Proceedings of the Run II QCD and Weak Boson Physics Workshop, hep-ex/0005012.


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Q: Laravel 5 and Github Integration I've found an interesting package for Laravel 5 at https://github.com/GrahamCampbell/Laravel-GitHub an thought of giving it a try. The only problem is the lack of documentation. I was just wondering if anyone knows or could point point me the way how I can go about using the package.
I'm particularly keen on the concept of getting the latest commits done on particular repository rather than oAuth client or such.
Anybody here got an idea?

redpajama_set_name: RedPajamaStackExchange


Time was short to seek out the Warblers and other species before they left our area. A walk was scheduled for this date although to mixed reviews as to what may be found. All the rain & overcast last week wasn't helpful in terms of getting outside; it also had all the plant life sprouting and many more leaves were on the trees.
We had a terrific group of people on this walk and it was well attended. I was really pleased to see Bob from York Audubon and Stan and his wife from the Stanton Bird Club based in Lewiston. I've learned much and met some great folks in the last few weeks at these morning events. I'd be unwilling to guess at the combined years of knowledge & experience gathered at Evergreen Cemetery on this Wednesday. We were also joined by my friend Paul; we traveled in together & he had his camera, long lens and tripod to do some digital capture.
I'd expected a beautiful blue morning just as predicted with lots of bird activity energized by the sun. However, this was not to be and the Sun was barely able to break the cloud cover making it a bit dismal as we walked the paths around the ponds. There were many birds about and although not as concentrated as the weeks before many remained available to view.
I'd been attempting to get a better image of a Chestnut-sided Warbler over the last few weeks. This image isn't perfect but it represents an improvement. Paul and I laughed when he realized how difficult it can be to follow one of these smallish birds with a long lens. After following this bird around a bit, he finally broke cover enough for this exposure.
There were more American Redstarts around than I'd viewed in the last few weeks. After some time stalking a pair I was able to image this beautiful female.
Among the warblers were we viewing as we hiked along were the usual contingent of Yellow-rumped Warblers. Bob indicated those we were seeing were formerly referred to as Myrtle Warblers. Along with their cousin (formerly known as) the Audubon Warbler, they were grouped into a species now known as the Yellow-rumped Warbler. This makes the Myrtle and Audubon subspecies. I'm referencing the older designation here in the image but this bird is a Yellow-rumped Warbler. I got several exposures on this female although the gray sky background wasn't conducive to a great image.
The best group of images for the morning included a pair of Canada Warblers frolicking in a tree not far from where the group passed. A fellow making the morning tour (with his son in a backpack carrier no less) was checking out the activity in a tree - the bulk of the group had passed the spot and it was quiet. I walked over to check out what he was doing and viewed several warblers flitting about. It only took an instant to drop the tripod and as soon as I obtained a relatively unobstructed view through the lens took a series of exposures. The results - the best of the morning can be viewed below. I was really pleased to have another opportunity to image this striking bird.
Another view of a feisty Chestnut-sided Warbler at Evergreen. Although not nearly as abundant, there were still many warblers in the area.
It was actually a good day for birding at Evergreen although not an especially auspicious one for camera work. Paul or I didn't take many shots, perhaps half or less of what I generally shoot over several hours. The ratio of exposures to 'keepers' wasn't good for this day but it's always worthwhile and I'm pleased I found the time to get out.
I didn't take any sighting notes but noticed many in the group did. I'm planning to start carrying my voice recorder in lieu of attempting to write in the field. With the tripod, camera and lens to carry plus my second camera on a strap over my shoulder, my hands are full enough as is. See the link at the bottom of this section to view the sightings list.
There were several groups in the field besides ours and I commented that I'd been around enough lately with camera in hand that I was becoming quite familiar with many faces in our local birding community. As Bob indicated, most of the people are really great and just as in astronomy, everyone is willing to help out if you have questions.
I wish to thank all our walk attendees for making this a fun time. I offer a special thanks to Bob from the York Chapter and my friend Stan from the Stanton Bird Club. Spending time with you guys is wonderful and a terrific learning experience.
The list of sightings for the day can be found at Merrymeeting Audubon Trip Reports. Please take a look if you have an opportunity.


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I want to take some time to talk about a problem that plagues most people who exercise regularly. A cramp can seriously hinder your workout routine and can even wake you up in the middle of the night. But what is a cramp? What causes them? And can they be prevented?
The term "cramp" stems from the German/Norse root meaning –squeezing, pressing, or pinching uncomfortably. "Exercise Associated Muscle Cramps" [EAMC] are defined as –spasmodic, painful, involuntary contraction of the skeletal muscle that occurs during or immediately after exercise. The term EAMC is used to differentiate between these and other types of cramps. EAMC represents a wide range of both pain levels and duration. They can last anywhere from seconds to as long as hours. The general practice is to wait them out; however, if you are in an sport event or exercise class, you may not have the time. Muscle cramps can feel like a slight stinging or can represent excruciating pain. When severe, cramps may result in a bruise on the skin. While cramps can occur in any muscle, there are factors that make them more likely. Cramps usually occur in muscles that cross two joints. The most common areas for cramps are the calves, hamstrings, quads, feet, hands, arms, and abdomen.
It seems perplexing that something so common and debilitating doesn't have a definite cause; however, researchers have yet to identify one. The problem is that without a cause, cramps are difficult to prevent. Common theories behind cramps include dehydration, electrolyte depletion, poor conditioning, and fatigue. In a 2004 study, a majority of these theories were discredited. After conducting a review of the current research regarding EAMC, Martin Schwellnus of the University of Cape Town, posits that the altered neuromuscular control is the most plausible theory. He concludes "Whilst it is clear that further evidence to support the "altered neuromuscular control" hypothesis is also required, research data are accumulating that support this as the principal pathophysiological mechanism for the etiology of exercise-associated muscle cramping (EAMC)." Altered neuromuscular control is related to muscular fatigue and results in a disruption of muscular coordination and control.
Without getting bogged down in physiology, every muscle receives a signal to contract from an alpha motor neuron. This neuron fires, stimulating the contraction; however, other fibers exist to prevent over-stretching of a muscle (muscle spindles) and a contraction that is too forceful (Golgi tendon organs). When a muscle fatigues, the interplay between these contrasting organs is changed. The alpha motor neuron fires as planned, yet the protective fibers (muscle spindles and Golgi tendon organs) receive less stimulation. The result is a muscle that continues to contract, without any limiting factors; thus, "an involuntary contraction." Without a definite cause of EAMC, treatment patterns vary.
Cramps will naturally go away in due time; however, remedies to speed this process in the athletic population have been determined. First, the athlete should stop activity immediately. Fluids containing carbohydrates should be ingested. The affected muscles should be passively stretched, and the joint should maintain an extended position. It is common for the pain to decrease in severity and subsequently flare up repeatedly before it fully subsides.
Here are a few factors that may lead to cramps. Older age, longer history of running, higher BMI, shorter daily stretch routine, increased environmental temperature and humidity, and engaging in new activities are all considered risk factors.
Cramps have historically plagued athletes and the common exerciser alike. I hope this information helps.
I'm not getting sore after I lift anymore. Am I still getting a good workout?
A common misconception in the fitness industry is that muscle soreness is the sole indicator of a great workout. However, muscle soreness is not a prerequisite for muscle growth or a great workout! In fact, muscle soreness should rarely be your goal. Many experts suggest that a certain amount of damage seems to be required for maximum hypertrophy (muscle growth). But the damage need not be so intense that you regularly encounter soreness. During the initial phase of training, some degree of soreness will most likely be experienced. To minimize soreness, warm up before exercise, do not over emphasize eccentric contractions (lengthening of the muscle) and begin with a low to moderate whole body approach, progressing to greater intensities.
You may want to consider how long you have been on the current exercise routine. Changing something (i.e. weight, stability requirements, rep scheme, or rest intervals) may produce a more effective exercise session.
No matter how young or old you are, this is a great philosophy to enact. Have a great week everybody.
In today's world, many businesses are trying to incorporate technological advances as a means to improve their product. Schools are going electronic and even the government accepts email versions of formal documents. But how is the world of exercise and physical fitness keeping up?
I agree that there are a number of workout apps that offer a quick fix for people who are lost in a gym. The problem is that the app can't really track your action nor determine if your physical activity report is genuine (aside from GPS-based running apps). Some people even buy into programs where they submit money and get a refund only by meeting their weekly exercise goal.
The real issue, as with everything else in life, is motivation. What can a person obtain from their exercise program? For people with knowledge of the physiological and mental benefits of exercise, it is simple to understand that exercise is a necessary part of life. But, other people only look for a change in the scale or a vast improvement in strength.
As a psychology double major, I learned the benefits of a reward system and how it can influence motivation and ultimately empower action. A great starting point to an exercise reward system is something that I recently saw in Russia. As a precursor to the Olympics and encouraging a nation to value exercise, they have developed a machine that will accept 30 squats as a payment for a subway pass.
This video shows the setup of the machine which uses a force plate and camera to count the number of squats. You can see the simple joy that people get from a "free" subway ticket.
Exercise has many positive effects of emotion and leads to a healthier person. (Notice the people smiling) Russia has taken the first step towards a potentially groundbreaking idea. I'm not saying that we should monetize exercise, but its a start.
A new research study out of Spain is promoting the benefits of watermelon in improving exercise recovery. Scientists studied the effects of watermelon juice, which is high in the amino acid L-citrulline. They determined that when consumed in its natural, unpasteurized form, watermelon juice helped to reduce muscle soreness and heart rates following exercise. The effect was significant when compared to both pasteurized watermelon juice and a placebo drink.
The specific mechanism of action has yet to be identified; however, it likely has to do with L-citrulline's removal of lactate. The more efficiently lactate is removed, the quicker the body recovers from exercise. Previous studies have determined the benefits of L-citrulline supplementation on lactic acid removal.
While watermelon makes for a great treat on a warm day, be sure to add some to your post-exercise meal.
Most bye weeks in the NFL are filled with a bit of relaxation and rehabilitation for the players as well as game planning and preparation. In possibly a worst case scenario, the Denver Broncos return from the bye week without their head coach. John Fox will have to undergo heart surgery to replace his aortic valve. He began feeling symptomatic while playing golf this past week and was immediately taken to the hospital. This is a very serious matter and its best that he receives immediate medical attention. I wanted to take some time today to discuss the anatomy and function of the heart.
The heart has four chambers: two atria and two ventricles. Valves open and close to allow blood to flow from one chamber to the next. They must seal shut to keep these chambers separate and prevent blood from going backwards through the heart.
The flow of blood is essential to understanding the function of the heart. As blood comes enters, it first reaches the right atrium then proceeds to the right ventricle. It pumps through the pulmonary valve to the lungs where the blood is infused with oxygen. When the oxygen-rich blood returns to the heart, it enters the left atrium. It finally reaches the left ventricle before exiting the aortic valve. The blood leaves the heart through the aorta and pumps to the rest of the body.
As I mentioned, the integrity of the heart valves keeps the blood flowing in the right direction and ensures the heart is functioning properly. In the case of John Fox, the aortic valve wasn't functioning properly. This could lead to a build-up of blood following a contraction, called afterload. The problem is that not enough blood is pumped out, leaving a reservoir in the ventricle. Surgical options include a mechanical valve replacement or replacement with a pig or horse valve.
The heart is arguably the most important organ and muscle in the human body. To keep it functioning properly, be sure to engage in aerobic exercise at least 3 times a week.


San Juan Community Home Trust (Trust) recycled twelve homes with historic character for the second phase of the Sunrise permanently affordable housing development. The neighborhood features reclaimed homes from Victoria, Canada moved by barge and track vehicle to their current locations in Friday Harbor, Washington. Homes were inspected by engineers for integrity before transport and permitted as renovations to existing structures.
All structures moved into place at Sunrise II were considered existing structures, so only needed permits for updates and renovations. This required approved foundation plans, utility rough-in inspections and permits for decks and outdoor walkways. Because the homes were constructed prior to 1940, they had "stood the test of time" according to permitting official Mike Bertrand. This reduced some planning phase work including drafting blueprints. By working with a firm out of Vancouver, BC that specializes in moving homes over water - Nickel Bros. - local firm Ravenhill Construction gained experiencein home recycling, moving from Victoria to Friday Harbor, learning to identify engineering best practices for longevity and structural integrity. The 12 units are considered condominiums within the three phase Sunrise development on the edge of Friday Harbor on land owned by the Trust and approved in a multi-phase development of 120 units.
2012 Washington Residential Code, section 102.7.2 requires moved buildings to comply with all codes, except if the use classification is unchanged, and the original building is not substantially remodeled. Homes were existing moved structures without substantial remodel, so building officials required developers to follow the town building permit guidelines for foundation planning, rough in utilities, and exterior features including decking; but other requirements did not apply due to exception in 102.7.2.
The Sunrise II neighborhood is a recycled home community installed in an 8 unit per acre density with common foot paths between shared remote parking. The whole development follows Low Impact Development standards, including rainwater catchment and stormwater mitigation ponds for street runoff. In 2017, gravel roads serve as pathways between the neighborhoods and as parking lots. The community is pursuing Net-Zero recognition, employing solar, LEDs and developing a water reclamation facility to reduce strain on municipal water resources. The community includes both one and two story homes with new additions of exterior walkways to fit new locations and some interior renovations to improve livability. Most of the work on each home was finishing details after installing plumbing and electrical connections. The demolition crews removed lower sections of wall to expose utilities, and retrofits were made on site in Friday Harbor. The homes are all unique to one another and given the name of the street where they were originally located in Victoria.
The San Juan Island community is a unique refuge for Western Washingtonians who seek a life off the I-5 corridor. With more sunny days and an arid climate compared with the nearby Skagit valley, the island is a vacation destination for thousands of tourists every summer. The service and tourism industry continues to grow, causing an increasing demand for affordable housing options in the community. Friday Harbor is expanding housing options with annexation of the 15 acre Sunrise community site. Sunrise seeks to create an opportunity for families to build equity on moderate income while living in Friday Harbor. Increasingly a retirement community, year-round service sector jobs for an aging community require affordable long-term housing options.
Classified as a condominium community on land owned by the Trust, the three phase development permit was conditional to increase affordable housing on the islands. A county government with strict development regulations to maintain the rural and private nature of the island community, this recent annexation area by the Town of Friday Harbor encouraged maximum density for service employees and other low to moderate income full-time residents. To qualify as a lessor in Sunrise, applicant's annual income must be 80-120% of the median county income of about $33,000, between about $26,000 and $40,000.
Nickel's Bros. "rescues" homes from demolition and delivers to various locations near the Salish Sea shoreline. The Trust contracted with Nickel's Bros. construction to purchase the homes and ship them across the Canada/United States border to the city of Friday Harbor. Ravenhill Construction indicated interest in single family homes built between 1900 and 1940 which would be good candidates to transport. These homes followed modest compact designs and kept appropriate building footprints for the permanently affordable community.
Over the next several months, Nickel's Bros contacted Ravenhill with opportunities to shop for homes. Public ferry service from Friday Harbor to Victoria Canada simplified crossing the international boundary for engineering inspections. As homes were purchased, Nickel's Bros transported houses on track vehicles taking special precautions for power lines and other delicate infrastructure. Most city streets accommodate the track vehicles but the gravel pathway at Sunrise was too narrow so the Trust rented a throughway from neighboring landowners to deliver the homes to their site in the community.
Upon arrival to the site, construction crews suspended the homes above their new resting places and then poured foundations. This allowed accuracy for the building of the foundations for the home's new site. Once the homes were lowered onto the cured foundations, finishing crews renovated the necessary plumbing and electrical for more modern applications and utility. These renovations included rewiring and plumbing, adding pop-out additions and exterior decks and walkways, replacing previously removed drywall, updating flooring and other aesthetic features.
This project was not about saving money on construction. The concept of saving materials from the waste stream and creating a historic character to the community were both considered and valued in the process.
As the project unfolded, engineers at Ravenhill developed skills and experience in selecting homes suitable for this kind of move, an opportunity to offer consulting to other Nickels Bros. clients shopping for movable homes.
This model allows owners of the condominiums to build equity on their investment and establish permanence in their community. A resale formula governs future exchanges of ownership, allowing for the homes to be deemed permanently affordable. The financial accessibility is supported by investments from community members who value an opportunity to create a sustainable long-term and diversified community with contributing members in all stages of life.
The engineering inspection is an important phase to develop when purchasing a recycled home. A qualified and detail oriented inspector should utilize a checklist to make sure the critical utilities and home functions are operational and comply with building codes. The team realized after purchasing and delivering one of the homes that it was wired with aluminum, which has been identified as neither best practice or safe. A full building electrical retrofit was required and expensive.


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The Aurora Research Institute Speaker Series was developed to strengthen public awareness of research taking place in the north and to engage northerners in the dialogue. It also provides opportunities for northern youth to access research and researchers, and hopefully be inspired to become involved in northern research.
Presentations are held at the Aurora Research Institute throughout the year. The Western Arctic Research Centre hosts an annual Summer Speaker Series to highlight the many research teams and projects in the region.
Virtual Speaker Series
In 2020, the ARI speaker series transitioned to virtual delivery. Upcoming virtual speaker series events are advertised through our Facebook page.
Upcoming Speaker Series
Here is the link to register for December 16, 2021 speaker series event
https://us02web.zoom.us/webinar/register/WN_eiyftXLlQES0a_u87ZhWag
Click on the links (or images) below to view recordings of our 2020 - 2021 webinar series.
November 11, 2020 - Minerals Strategy Geographic Information Systems (MSGIS) Tool Demonstration
January 13, 2021 - Addressing Women's Health in the NWT
March 4, 2021 - Cardboard Fuel Pellets: Feasibility through to Pilot
March 30, 2021 - Collaborative Beluga Research in the Inuvialuit Settlement Region
April 8, 2021 - Assessing Arctic Air
April 21, 2021 - Developing a Permafrost Research Program along the Inuvik-Tuktoyaktuk Highway
May 4, 2021 - Weather on Other Worlds: Massive Storms and Rains of Molten Iron
May 19, 2021 - Arctic Salmon: The Ups and Downs of Pacific Salmon in the Arctic Ocean
September 23, 2021 - The effects of permafrost thaw on carbon movement in freshwater streams of the Western Arctic
November 17, 2021 - Archaeology and Climate Change: Mapping threats to Inuvialuit Ancestral Sites
December 16, 2021 - Preserving our Ways of Life While not being "Left Behind"
Check the ARI Facebook page for a listing of topics, dates, and times.


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So It's been eight months…what?
Just got two of the cabinet doors back from being repaired. Slow and steady wins the race? Next time you hear me say that…shoot me.
Drapes are up though and we just need one more piece of art and it will be complete.


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Q: Tengo un input number y cuando un usuario ingresa por ejemplo 20. el resultado es vacío

function events(element){
      console.log(element.value)
    }
 <input type="number" step=".1" min="1" max="100" oninput="events(this)">

Resultado obtenidos

*

*20 = correcto

*20.5 = correcto

*20,5 = correcto

*20, = correcto y me retorna 20

*20. = incorrecto y me retorna vacío
Resultado esperado

*

*

*= correcto y que me retorne 20

A: Lo que debes hacer, es parsear a float el value de input, para convertirlo a numero.
var a = parseFloat("20");
var b = parseFloat("20.");
var c = parseFloat("20,");

Output: